Dynamic Pricing of Substitutable Products in the Presence of Capacity Flexibility

Firms that offer multiple products are often susceptible to periods of inventory mismatches where one product may face shortages while the other has excess inventories. In this paper, we study a joint implementation of price- and capacity-based substitution mechanisms to alleviate the level of such inventory disparities. We consider a firm producing substitutable products via a capacity portfolio consisting of both product-dedicated and flexible resources and characterize the structure of the optimal production and pricing decisions. We then explore how changes in various problem parameters affect the optimal policy structure. We show that the availability of a flexible resource helps maintain stable price differences across products over time even though the price of each product may fluctuate over time. This result has favorable ramifications from a marketing standpoint because it suggests that even when a firm applies a dynamic pricing strategy, it may still establish consistent price positioning among multiple products if it can employ a flexible replenishment resource. We provide numerical examples for the price stabilization effect and discuss extensions of our results to a more general multiple product setting

Dynamic Pricing and Replenishment with Customer Upgrades

We study a joint implementation of price‐ and availability‐based product substitution to better match demand and constrained supply across vertically differentiated products. Our study is motivated by firms that utilize dynamic pricing as well as customer upgrades, as ex ante and ex post mechanisms, respectively, to mitigate inventory mismatches. To gain insight into how offering product upgrades impacts optimal price selection, we formulate a multiple period, nested two‐stage model where the firm first sets prices and replenishment levels for each product while the demand is still uncertain, and after observing the demand, decides how many (if any) of the customers to upgrade to a higher quality product. We characterize the structure of the optimal upgrade, pricing and replenishment policies and find that firms having greater flexibility to offer product upgrades can restrain their reliance on dynamic pricing, enabling them to better protect the price differentiation between the products. We also show how the quality differential between the products or changes in the replenishment cost structures influence the optimal policy. Using insights gained from the optimal policy structure, we construct a heuristic policy and find that it performs well across various parameter values. Finally, we consider an extension in which the firm dynamically sets upgrade fees in each period. Our results overall help further our understanding of the intricate relationship among a firm's decisions on pricing, replenishment, and product upgrades in an effort to better match demand and constrained supply

Comments on the RGGI Market Design

Auctions, carbon auctions, greenhouse gas auctions

Demand Estimation at Manufacturer-Retailer Duo: A Macro-Micro Approach

This dissertation is divided into two phases. The main objective of this phase is to use Bayesian MCMC technique, to attain (1) estimates, (2) predictions and (3) posterior probability of sales greater than certain amount for sampled regions and any random region selected from the population or sample. These regions are served by a single product manufacturer who is considered to be similar to newsvendor. The optimal estimates, predictions and posterior probabilities are obtained in presence of advertising expenditure set by the manufacturer, past historical sales data that contains both censored and exact observations and finally stochastic regional effects that cannot be quantified but are believed to strongly influence future demand. Knowledge of these optimal values is useful in eliminating stock-out and excess inventory holding situations while increasing the profitability across the entire supply chain. Subsequently, the second phase, examines the impact of Cournot and Stackelberg games in a supply-chain on shelf space allocation and pricing decisions. In particular, we consider two scenarios: (1) two manufacturers competing for shelf space allocation at a single retailer, and (2) two manufacturers competing for shelf space allocation at two competing retailers, whose pricing decisions influence their demand which in turn influences their shelf-space allocation. We obtain the optimal pricing and shelf-space allocation in these two scenarios by optimizing the profit functions for each of the players in the game. Our numerical results indicate that (1) Cournot games to be the most profitable along the whole supply chain whereas Stackelberg games and mixed games turn out to be least profitable, and (2) higher the shelf space elasticity, lower the wholesale price of the product; conversely, lower the retail price of the product, greater the shelf space allocated for that product

Asymmetric Pricing and Replenishment Controls for Substitutable Products

We study settings in which a firm offering substitutable products may face restrictions in its ability to either replenish or adjust the prices of some of its products, resulting in asymmetries in the pricing and replenishment controls available for each product. Specifically, we first consider a firm selling two substitutable products, a seasonal and a regular product, that differ in how their inventories are managed over a finite selling horizon. The seasonal product has an initial inventory with no further replenishment opportunities and is dynamically priced throughout the selling horizon, whereas the regular product has a static price but can be replenished periodically subject to a limited capacity. We characterize the firm’s optimal replenishment decision for the regular product as well as the dynamic pricing and initial quantity selection decisions for the seasonal product. Through the insights gained by the optimal policy structure, we also develop a simple-to-implement and effective heuristic policy. In addition, we investigate profit implications of markdown policies and study how potential differences in quality perceptions between the products impact the optimal policy. Lastly, we consider further types of asymmetries resulting in pricing with partial replenishment or replenishment with partial pricing and provide insights on the value of additional pricing and replenishment flexibilities. Our study helps broaden our understanding of joint pricing and replenishment decisions for substitutable products under circumstances where these decisions may not all be available for all products

Dynamic pricing policies for interdependent perishable products or services using reinforcement learning.

Many businesses offer multiple products or services that are interdependent, in which the demand for one is often affected by the prices of others. This article considers a revenue management problem of multiple interdependent products, in which dynamically adjusted over a finite sales horizon to maximize expected revenue, given an initial inventory for each product. The main contribution of this article is to use reinforcement learning to model the optimal pricing of perishable interdependent products when demand is stochastic and its functional form unknown. We show that reinforcement learning can be used to price interdependent products. Moreover, we analyze the performance of the Q-learning with eligibility traces algorithm under different conditions. We illustrate our analysis with the pricing of services

Inventory and pricing management in probabilistic selling

Context: Probabilistic selling is the strategy that the seller creates an additional probabilistic product using existing products. The exact information is unknown to customers until they receive the probabilistic products. This strategy is still a relatively new area for both researchers and practitioners. Many of the corresponding operations problems need to be solved to take full advantage of the opportunity of this innovative marketing strategy. However, limited attention has been paid to examining the inventory management of probabilistic selling from the perspective of Operations Management, which cannot meet the needs of decision-making in reality. Objectives: Considering different characteristics of the probabilistic product, the buyer, and the seller involved in probabilistic selling, i.e., the probabilistic product form, the buyers’ behaviours of demand switch and barter exchange, and the seller's product allocation behaviour, we establish models and solve the decision problems of pricing, inventory, joint decision of pricing-inventory, and product allocation, etc. Based on the analysis of optimal decisions and strategy comparison results, we shed some lights on the effectiveness of probabilistic selling on managing uncertainty, and its profitability. Method: First, we analyze the practice scenarios of probabilistic selling. Next we mainly use newsvendor inventory model, hotelling model, and optimization theory to model, solve, and analyze the operational problems. Then we give some analytical results. Next we conduct the numerical analysis using softwares of Matlab and Mathematica. Finally, we provide insightful managerial implications for the practice of probabilistic selling. Results: The thesis derives the optimal operational decisions of inventory order, pricing, inventory allocation, and product line design in probabilistic selling. Overall, the analysis of the results show that probabilistic selling can benefit the seller with higher expected profit by reducing demand/supply uncertainty and improving inventory efficiency. The performance of probabilistic selling is closely dependent on customers' price sensitivity, product similarity, and uncertainty level, etc. Main results considering different research scenarios are as follows: 1) When the price for the probabilistic product is independent on demand reshape, a proper cannibalization can benefit the retailer in terms of yielding a higher expected profit. Probabilistic selling is more profitable with relatively lower product similarity and higher price-sensitive customers, while inventory substitution strategy outperforms probabilistic selling with higher product similarity. 2) When the price for the probabilistic product is dependent on demand reshape, probabilistic selling can benefit the seller with higher expected profit and lower inventory. Probabilistic selling is more profitable with lower product differentiation, higher customers' price sensitivity, and higher demand uncertainty. Improper pricing would undermine the seller's profit. 3) When the seller offers physical probabilistic product, he can benefit from two effects, namely the risk pooling effect due to demand reshape and the risk diversification effect due to inventory flexibility. 4) When the seller offers barter choice in probabilistic selling, he may benefit from the marketing effect in the barter process. Offering barter choice can broaden the application range of probabilistic selling, which will increase with successful barter probability. Conclusions/Implications: First, the thesis helps sellers understand how to manage their inventory, pricing and related implementation issues to take full advantage of probabilistic selling. Second, this thesis explores the mechanism of this innovative marketing strategy as an inventory management tool to combat uncertainty which also riches the literature on Operations Management, especially inventory management.Antecedentes: Los productos probabilísticos son productos adicionales creados por un proveedor que combina productos existentes y oculta parte de la información del producto. Es decir, cierta información de atributos de los productos probabilísticos es opaca para el cliente. El cliente que compra el producto probabilístico obtiene una de las combinaciones de productos con una cierta probabilidad. Las ventas probabilísticas son una estrategia de ventas que permite la venta de productos probabilísticos. Todavía es un modelo de ventas relativamente nuevo para empresas e investigadores. La implementación de ventas probabilísticas es diversa y aún no se ha verificado la rentabilidad de las diferentes formas de ventas probabilísticas. Se deben abordar las situaciones de inventario y fijación de precios que tengan en cuenta las diferentes realidades. Por el momento, desde la perspectiva de la gestión operativa, existen pocos estudios sobre la toma de decisiones de inventario y fijación de precios bajo el modelo de ventas probabilísticas, que no puede satisfacer las necesidades de las empresas para tomar decisiones científicas en el proceso de implementación. Objetivo: Este documento se centra en los tres actores principales en el proceso de venta probabilística: los productos probabilísticos, compradores y vendedores. Considere el afecto de las diferentes realidades y circunstancias (en concreto, la forma de productos probabilísticos, la demanda de transferencia y el comportamiento de intercambio del comprador, y si el vendedor reemplaza el producto en el proceso de distribución de los productos) sobre la fijación de precios y las decisiones de inventario. Al establecer un modelo que considera los factores realistas antes mencionados, se resuelve el problema de fijación de precios, la decisión conjunta de inventario- precios y la asignación de productos bajo el modelo probabilístico de ventas. Finalmente, a través del análisis de las decisiones y la comparación de estrategias, se obtendrá sugerencias de gestión para la implementación de ventas probabilísticas. Método: En primer lugar, este documento analiza los escenarios de diferentes ventas de probabilidad. En segundo lugar, utilizando el modelo de vendedor de periódicos, el modelo de Hotelling y la teoría de optimización, se intenta resolver y analizar la fijación de precios, el inventario, la toma de decisiones conjunta de inventario-precios y los problemas de decisión de asignación de productos. Luego, da el teorema y analízalo. Finalmente, proporcione asesoramiento de gestión de inventario- precios para los comerciantes que implementan ventas probabilísticas. Conclusión: Este documento ha encontrado las decisiones operativas óptimas para el inventario, fijación de precios, asignación de inventario y diseño de línea de producto en ventas probabilísticas. Los resultados generales muestran que las ventas probabilísticas pueden aumentar la eficiencia del inventario al reducir la incertidumbre de la demanda / oferta, lo que permite a los vendedores obtener mayores ganancias esperadas. El rendimiento de las ventas probabilísticas está estrechamente relacionado con factores tales como la sensibilidad del precio del cliente, la similitud y la incertidumbre del producto. Significado: Primero, permita que los vendedores hagan un buen uso de las ventas probabilísticas. Este artículo los ayuda a comprender cómo resolver problemas de inventario, precios y decisiones operativas relacionadas en modelos de ventas probabilísticas. Segundo, consideramos esta estrategia de marketing innovadora como una herramienta de gestión de inventario, por lo que este documento enriquece la investigación de gestión operativa, especialmente la teoría de gestión de inventarioPostprint (published version

Amazon and Platform Antitrust

With its decision in Ohio v. American Express, the U.S. Supreme Court for the first time embraced the recently developed, yet increasingly prolific, concept of the two-sided platform. Through advances in technology, platforms, which serve as intermediaries allowing two groups to transact, are increasingly ubiquitous, and many of the biggest tech companies operate in this fashion. Amazon Marketplace, for example, provides a platform for third-party vendors to sell directly to consumers through Amazon’s web and mobile interfaces. At the same time that platforms and their scholarship have evolved, a burgeoning antitrust movement has also developed which focuses on the impact of the dominance of these tech companies and the fear that current antitrust laws are ill-equipped to prevent any potential anticompetitive behavior. Many of those who feel this way worried that American Express, which decided whether a plaintiff alleging anticompetitive behavior by a two- sided platform would have to show harm to both sides of the market to make a prima facie case, would give companies like Amazon even more power. This Note argues that while the case could be interpreted in such a way, because Amazon and similarly situated platforms possess a great degree of control over their users—in some cases competing with them directly—it would be unwise to do so